New! View global litigation for patent families

US20040061710A1 - System for improving display resolution - Google Patents

System for improving display resolution Download PDF

Info

Publication number
US20040061710A1
US20040061710A1 US10447186 US44718603A US2004061710A1 US 20040061710 A1 US20040061710 A1 US 20040061710A1 US 10447186 US10447186 US 10447186 US 44718603 A US44718603 A US 44718603A US 2004061710 A1 US2004061710 A1 US 2004061710A1
Authority
US
Grant status
Application
Patent type
Prior art keywords
image
sampling
luminance
chromatic
pixel
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
US10447186
Other versions
US7110012B2 (en )
Inventor
Dean Messing
Scott Daly
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sharp Corp
Original Assignee
Sharp Laboratories of America Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
    • G06T3/40Scaling the whole image or part thereof
    • G06T3/4015Demosaicing, e.g. colour filter array [CFA], Bayer pattern
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09GARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G5/00Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators
    • G09G5/02Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators characterised by the way in which colour is displayed
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09GARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G2340/00Aspects of display data processing
    • G09G2340/04Changes in size, position or resolution of an image
    • G09G2340/0407Resolution change, inclusive of the use of different resolutions for different screen areas
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09GARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G2340/00Aspects of display data processing
    • G09G2340/04Changes in size, position or resolution of an image
    • G09G2340/0457Improvement of perceived resolution by subpixel rendering
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09GARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G3/00Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes
    • G09G3/20Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters
    • G09G3/2007Display of intermediate tones
    • G09G3/2059Display of intermediate tones using error diffusion
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09GARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G5/00Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators
    • G09G5/22Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators characterised by the display of characters or indicia using display control signals derived from coded signals representing the characters or indicia, e.g. with a character-code memory
    • G09G5/24Generation of individual character patterns
    • G09G5/28Generation of individual character patterns for enhancement of character form, e.g. smoothing

Abstract

A system for improving the display resolution by the reduction of chromatic aliasing.

Description

    BACKGROUND
  • [0001]
    The present applications claims the benefit of U.S. patent application filed May 9, 2003, U.S. Ser. No. 60/469,432 entitled System For Improving Display Resolution; claims priority of U.S. patent application Ser. No. 09/735,424 filed Dec. 12, 2000 which claims the benefit of 60/211,020 filed Jun. 12, 2000; claims priority of U.S. patent application Ser. No. 09/735,425 filed Dec. 12, 2000 which claims the benefit of 60/211,020 filed Jun. 12, 2000; claims priority of U.S. patent application Ser. No. 09/735,454 filed Dec. 12, 2000 which claims the benefit of 60/211,020 filed Jun. 12, 2000.
  • [0002]
    The present invention relates to the field of displaying high resolution images on displays with lower resolution.
  • [0003]
    The most commonly used method for displaying high-resolution images on a lower resolution color mosaic display is to prefilter and re-sample the pixels 2 of the high-resolution image 4 down to the resolution of the low-resolution display 6, as shown in FIG. 1. In the process, the R, G, B values of selected color pixels 8 are mapped to the separate R, G, B elements 10, 12 and 14 of each display pixel 16. These R, G, B elements 10, 12 and 14 of a display pixel are sometimes also referred to as subpixels. Because the display device does not allow overlapping color elements, the subpixels can only take on one of the three R, G, or B colors. The color's amplitude, however, can be varied throughout the entire grey scale range (e.g., 0-255). The subpixels often have a 1:3 aspect ratio (width:height), so that the resulting pixel 16 is square. The aforementioned subsampling/mapping techniques fail to consider the fact that the display's R, G, and B subpixels are spatially displaced; in fact the pixels of the low resolution image are assumed to be overlapping in the same manner as they are in the high-resolution image. This type of sampling may be referred to as sub-sampling, traditional sub-sampling, or ordinary sub-sampling.
  • [0004]
    The pixels of the high-resolution image 4 are shown as three slightly offset stacked squares 8 to indicate their RGB values are associated for the same spatial position (i.e., pixel), generally referred to as co-sited sub-pixels. One display pixel 16 on a color mosaic display, consisting of one each of the R, G and B subpixels 10, 12 and 14 is shown as part of the lower-resolution triad display 6 in FIG. 1.
  • [0005]
    In the example shown in FIG. 1, the high-resolution image has 3× more resolution than the display (in both horizontal and vertical dimensions). In the case that filtering is omitted, the subsampling process would cause undesirable aliasing artifacts, and, accordingly, various methods are used, such as averaging the neighboring un-sampled pixels in with the sampled pixel, to reduce the aliasing. In addition, the subsampling technique of FIG. 1 results in mis-registration of the color fields each of which carries a portion of the luminance information. This leads to a loss of luminance resolution attainable at the sub-pixel sampling rate.
  • [0006]
    It is noted that the technique of weighted averaging of neighboring elements while subsampling is mathematically equivalent to prefiltering the high resolution image. Also, it is noted that techniques of selecting a different pixel than the leftmost (as shown in FIG. 1) can be considered as a prefiltering that affects only phase. Thus, most of the processing associated with reducing aliasing may be viewed as a filtering operation on the high-resolution image, even if the kernel is applied only at the sampled pixel positions, or both.
  • [0007]
    It has been realized that the aforementioned techniques do not take advantage of potential display resolution. Information regarding potential display resolution is discussed by R. Fiegenblatt (1989), “Full color imaging on amplitude color mosaic displays” Proc. SPIE V. 1075, 199-205; and J. Kranz and L. Silverstein (1990) “Color matrix display image quality: The effects of luminance and spatial sampling,” SID Symp. Digest 29-32, incorporated herein by reference.
  • [0008]
    For example, in the display shown in FIG. 1, while the display pixel 16 resolution is ⅓ that of the pixel resolution of the high resolution image (source image) 4, the subpixels 10, 12 and 14 of the low resolution image are at a resolution equal to that of the high resolution image (in the horizontal dimension). This may be taken advantage of as shown in FIG. 2. In the case that the low resolution display were to be viewed solely by a color blind individual, he would see it as a higher resolution image than if ordinary sub-sampling is used. In essence, a luminance value exists for each pixel of the high resolution image which is mapped to a corresponding sub-pixel of the low resolution image. In this manner, a portion of the high resolution luminance image 4 is preserved in the sub-pixels of the low resolution image. This approach is shown in FIG. 2, where the R, G, and B subpixels 10, 12 and 14 of the low resolution display are taken from the corresponding colors of different pixels 11, 13 and 15 of the high-resolution image. This allows the sub-pixel horizontal resolution of the low resolution display to be at the pixel resolution of the high resolution display. Sampling which comprises mapping of color elements from different image pixels to the subpixels of a display pixel triad may be referred to as sub-pixel sampling.
  • [0009]
    But what about the viewer of the display who is not color-blind? That is, the majority of viewers. Fortunately for display engineers, even observers with perfect color vision are generally color blind at the highest spatial frequencies. This is indicated in FIG. 3, where idealized spatial frequency responses of the human visual system are shown.
  • [0010]
    In FIG. 3, luminance Contrast Sensitivity Function (CSF) 17 refers to the achromatic content of the viewed image, and chrominance CSF 19 refers to the color content, which is processed by the visual system as isoluminant modulations from red to green, and from blue to yellow. The color difference signals R-Y and B-Y of typical video are rough approximations to these modulations. For most observers, the bandwidth of the chromatic frequency response is ½ that of the luminance frequency response. Sometimes, the bandwidth of the blue-yellow modulation response is even less, down to about ⅓ of the luminance.
  • [0011]
    With reference to FIG. 4, in the horizontal direction of the display, there is a range of frequencies that lie between the Nyquist frequency of the display pixels 16 (display pixel=triad pixel, giving a triad Nyquist at 0.5 cycles per triad pixel) and the Nyquist frequency of the sub-pixels 10, 12 and 14 (0.5 cycles per subpixel=1.5 cycles/triad pixels). This region of frequencies is shown as the rectangular region 20 in FIG. 4. The result of convolving the high resolution image with a rect function whose width is equal to the display sample spacing is shown as a dashed-dot curve 22. This is the most common approach taken for modeling the display MTF (modulation transfer function) when the display is a LCD.
  • [0012]
    The result of convolving the high-res source image with a rect function whose width is equal to the subpixel spacing is shown as a dashed curve 24, which has higher bandwidth. This is the limit imposed by the display considering that the subpixels are rect in ID. In the shown rectangular region 20, the subpixels can display luminance information, but not chromatic information. In fact, any chromatic information in this region is aliased. Thus, in this region, by allowing chromatic aliasing, the display may achieve higher frequency luminance information than allowed by the triad (i.e., display) pixels. This is the “advantage” region afforded by using sub-pixel sampling.
  • [0013]
    The sub-pixel sampling registers the luminance information in the three color fields of the displayed image. Mis-registration as a result of displaying the image causes loss of luminance resolution while sub-pixel sub-sampling reduces it. The sub-sampling prefilter applied to the image may be sufficiently broad to permit the high resolution luminance information to pass. This additional luminance resolution will not result in significant aliasing of the luminance information because the Nyquist frequency is determined by the sub-pixel sampling period. However, significant chromatic aliasing can occur because the chromatic Nyquist frequency is determined by the display sampling period. The “advantage” region may be thought of as where significant chromatic aliasing occurs and significant luminance aliasing does not occur.
  • [0014]
    For applications with font display, the black and white fonts are typically preprocessed, as shown in FIG. 5. The standard pre-processing includes hinting, which refers to the centering of the font strokes on the center of the pixel, i.e., a font-stroke specific phase shift. This is usually followed by low-pass filtering, also referred to as grey scale anti-aliasing.
  • [0015]
    The visual frequency responses (CSFs) shown in FIG. 3 are idealized. In practice, they have a finite falloff slope, more representatively shown in FIG. 6A. The luminance CSF 30 has been mapped from units of cy/deg to the display pixel domain (assuming a viewing distance of 1280 pixels). It is shown as the solid line 30 that has a maximum frequency near 1.5 cy/pixel (display pixel), and is bandpass in shape with a peak near 0.2 cy/pixel triad. The R:G CSF 32 is shown as the dashed line, that is lowpass with a maximum frequency near 0.5 cy/pixel. The B:Y CSF 34 is shown as the long dashed LPF curve with a maximum frequency similar to the R:G CSF, but with lower peak response. The range between the cutoff frequencies of the chroma CSF 32 and 34 and the luminance CSF 30 is the region where one may allow chromatic aliasing in order to improve luminance resolution. The chromatic aliasing will not be visible to the human eye because it falls outside the chromance CSF.
  • [0016]
    [0016]FIG. 6A also shows an idealized image power spectra 36 as a 1/f function, appearing in the figure as a straight line with a slope of −1 (since the figure is using log axes). This spectrum will repeat at the sampling frequency. The pixel repeat 38 is due to the pixel sampling rate, and the repeat 40 is due to the subpixel sampling rate. Note that the shapes of the repeat spectra are different than the 1/f base band spectra 36, because they are plotted on log-log axes. The portions of these repeat spectra 38 and 40 that extend below their respective Nyquist frequencies represent aliasing. The leftmost one is chromatic aliasing 38 since it is due to the pixel sampling rate, while the luminance aliasing 40 occurs at higher frequencies because it is related to the higher sub-pixel sampling rate.
  • [0017]
    In FIG. 6A, no prefiltering has been applied to the source spectra. Consequently, aliasing, due to the pixel sampling (i.e., chromatic aliasing), extends to very low frequencies 35. Thus even though the chromatic CSF has a lower bandwidth than the luminance CSF, the color artifacts will, in general, still be visible (depending on the noise and contrast of the display).
  • [0018]
    In FIG. 6B, a prefilter was applied (a rect function in the spatial domain equal to three source image pixels), shown in FIG. 4 as a dashed-dotted line 22, to the source power spectrum, and it affects the baseband spectrum 42 in the region of 0.5 cy/pixel and greater, causing it to have a slope steeper than −1 shown at 44. The steeper slope effectively reduces the effects of the chromatic aliasing. The repeat spectra 38 a and 40 a also show the effect of this prefilter. For example, the tail 35 (FIG. 6A) is dramatically reduced as tail 46 (FIG. 6B) with this filter. The visible chromatic aliasing, that is aliasing under the two chrominance CSFs 32 a and 34 a, is reduced. However, it can be observed that this simple luminance prefiltering also removes significant luminance resolution (e.g. the curve 44 (FIG. 6B) relative to curve 45 (FIG. 6A)).
  • [0019]
    To increase the luminance information a system may use the difference in the human visual system's luminance and chrominance bandwidth. This bandwidth difference in luminance and chrominance (CFSs) in FIG. 6B may be referred to as the “advantage region”. One technique to achieve such a boost is to design the prefiltering based on visual system models as described in C. Betrisey, et al (2000), “Displaced filtering for patterned displays,” SID Symposium digest, 296-299, incorporated by reference and illustrated in FIG. 7.
  • [0020]
    The Betrisey, et al. technique ideally uses different prefilters depending on which color layer, and on which color subpixel the image is being sampled for. There are 9 filters designed using a human visual differences model described in Zhang and B. Wandell (1996) “A spatial extension of CIELAB for digital color image reproduction,” SID Symp. Digest 731-734, incorporated herein by reference and shown in FIG. 7. This was done offline, assuming the image is always black and white. In the final implementation, three rect functions rather than the resulting nine optimal filters are used in order to save computations. In addition, there is still some residual chromatic error that can be seen because the chromatic aliasing extends down to lower frequencies than the chromatic CSF cutoff (as seen in FIG. 6B).
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • [0021]
    It is to be understood that these drawings depict only typical embodiments of the invention and are not therefore to be considered to be limiting of its scope. The invention will be described and explained with additional specificity and detail through the use of the accompanying drawings in which:
  • [0022]
    [0022]FIG. 1 is a diagram showing traditional image sampling for displays with a triad pixel configuration;
  • [0023]
    [0023]FIG. 2 is a diagram showing sub-pixel image sampling for a display with a triad pixel configuration;
  • [0024]
    [0024]FIG. 3 is a graph showing idealized CSFs plotted on a digital frequency axis;
  • [0025]
    [0025]FIG. 4 is a graph showing an analysis of the pixel Nyquist and sub-pixel Nyquist regions which denotes the advantage region;
  • [0026]
    [0026]FIG. 5 shows typical pre-processing techniques;
  • [0027]
    [0027]FIG. 6A is a graph showing an analysis using 1/f-power spectra repeated at pixel sampling and sub-pixel sampling frequencies;
  • [0028]
    [0028]FIG. 6B is a graph showing an analysis using 1/f-power spectra repeated at pixel sampling and sub-pixel sampling frequencies with effects due to pre-processing;
  • [0029]
    [0029]FIG. 7 is a block diagram showing a known use of a visual model;
  • [0030]
    [0030]FIG. 8 is a block diagram showing one embodiment of the present invention;
  • [0031]
    [0031]FIG. 9 is a block diagram showing another embodiment of the present invention which employs pre-processing;
  • [0032]
    [0032]FIG. 10 is a block diagram showing yet another embodiment of the present invention which uses filtering of separated luminance and chrominance channels;
  • [0033]
    [0033]FIG. 11 is a block diagram of another embodiment of the present invention which employs a visual model utilizing masking of chroma by luminance; and
  • [0034]
    [0034]FIG. 12 is a block diagram of another embodiment of the present invention using a visual model which utilizes masking of chroma by luminance with a more accurate multi-channel, divided-frequency range visual model.
  • [0035]
    [0035]FIG. 13 is another block diagram of another embodiment.
  • [0036]
    [0036]FIG. 14 illustrates a spatial frequency response.
  • [0037]
    [0037]FIG. 15 illustrates another spatial frequency response.
  • [0038]
    [0038]FIG. 16 is a block diagram of another embodiment.
  • [0039]
    [0039]FIG. 17 illustrates a sub-pixel sampling geometry.
  • [0040]
    [0040]FIG. 18 illustrates another sub-pixel sampling geometry.
  • DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
  • [0041]
    The preferred embodiments are best understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The figures listed above are expressly incorporated as part of this detailed description.
  • [0042]
    Elements of the system may be embodied in hardware, firmware and/or software. While exemplary embodiments revealed herein may only describe one of these forms, it is to be understood that one skilled in the art would be able to effectuate these elements in any of these forms.
  • [0043]
    It is readily understood that the components, as generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following more detailed description of the embodiments is not intended to limit the scope of the invention but it is merely representative of the embodiments.
  • [0044]
    An achromatic image, may be defined as an image having no readily visible color variation. This achromatic condition may occur when an image contains identical multiple layers or color channels thereby yielding a gray-scale image.
  • [0045]
    Embodiments may be described with reference to “RGB” images or domains, or “additive color domains”, or “additive color images.” These terms refer to any form of multiple component image domain with integrated luminance and chrominance information, including, but not limited to, RGB domains.
  • [0046]
    Embodiments may also be described with reference to “YCbCr” images or domains, “opponent color” domains, images or channels, or “color difference” domains or images. These terms refer to any form of multiple component image domain with channels which comprise distinct luminance channels and chrominance channels including, but not limited to, YCbCr, LAB, YUV, and YIQ domains.
  • [0047]
    Some embodiments are summarized in the block diagram shown in FIG. 8 wherein a high-resolution image, such as RGB high-resolution image 70, is modified. Unlike some known methods, the process is preferably not carried out solely in the RGB domain, although it could be. The YCrCb color domain may also be used, wherein the luminance and the chromatic components (Red-Green and Blue-Yellow) are separated. Any domain may be used, such as for example, approximations to the visual systems opponent color channels. Examples include CIELAB, YUV, and Y R-Y B-Y. Also, color domains where one or more channels have an enhanced luminance component with respect to the other channels may likewise be used. One potential measure of such enhancements is if a channel has >60%, >70%, >80%, >90%, or >95% of the luminance. In addition, the enhanced luminance color domain may be as a result of implicit processing in another color domain as opposed to a traditional color transformation from one color space to another. The luminance component is normally used for the detail. The chromatic components are modified so that after the sum 78 the compensated image 82 has false low frequencies that are of inverse sign to those that will be generated in sub-pixel sampling step 80, thus canceling in the final image sent to the display. Accordingly, low chromatic frequencies (i.e. the visible ones) are attenuated and high chromatic frequencies remain (i.e. the invisible one), eventually yielding a better sub-pixel sampled image that has fewer visible chromatic artifacts.
  • [0048]
    The system is described with respect to non-overlapping pixels, or otherwise spatially discrete color sub-pixels (e.g. color mosaic displays). However, the embodiments described herein may likewise be used with colors that are overlapping to a greater or lesser degree. Moreover, the images may be displayed using different sizes of pixels. In addition, while the preferred embodiments are described with respect to rectangular pixels and subpixels, other shapes of pixels and subpixels may likewise be used. Also, any particular pixel may be formed by a plurality of sub-pixels in any arrangement, some of which may be duplicated.
  • [0049]
    The system may be used to modify images which have been pre-filtered or which exist in a format or condition which does not require filtering, such as low-pass filtering. These particular embodiments may bypass any RGB pre-filtering steps and begin by processing an image with sub-pixel sampling.
  • [0050]
    Referring to FIG. 8 the high-resolution image may be defined in a manner such that the high-resolution image relative to a low-resolution image has more information content for a given portion of the image than the low-resolution image. The conversion process may be generally referred to as re-sampling. In some cases the low and high resolution images may be displayed on the same monitor, the same pixel spatial density, different sized monitors with the same number of pixels, etc. The high-resolution image 70 is sampled in a sub-pixel sampling simulation 72 to simulate the visible error caused by sub-pixel sampling. Since the sampling is preferably simulated, the resolution (i.e. the number of pixels) does not have to change, if desired. The error may be ascertained by comparing the original image 70 with the sub-pixel sampling simulation 72. The error may be isolated by subtracting 74, the simulation 72 from the original image 70. A visual model 76 may be used to reduce undesirable information, such as color aliasing. The result of the visual model may be used to modify the original image 70, for example, by introducing information representative of the visible error that is desirable to reduce in subsequent sub-pixel sampling. A modified error image is representative of the visible error, which is reduced during subsequent sub-pixel sampling. This modified error image is subtracted from the original image 70, and the result may be referred to as the compensated image 82 and is not limited to the 0-255 R, G, B range of the source image 70, as it allows for the use of negative values, if desired. For example, the compensated image may have a greater range of colors or be represented in a different manner.
  • [0051]
    The compensated image 82 is modified to remove additional information that is introduced, during the subsequent sub-pixel sampling 80. The compensated image 82 is then sampled using the sub-pixel sampling process 80 wherein the additional added information is reduced as a result of the sub-sampling process resulting in an improved lower-resolution image.
  • [0052]
    Accordingly, at least a portion of the visible error that is caused as a result of sub-pixel sampling is simulated and then identified in the high-resolution source image (or an image derived therefrom). The simulation of the visible error is preferably maintained at the same resolution as the higher resolution source image to simplify complexity. The visible error is preferably subtracted from the RGB image to create the compensated image 82. Accordingly, when such a corresponding visible error is introduced by the subpixel sampling process 80, it is reduced, at least in part, in the final image.
  • [0053]
    The system shown in FIG. 8 reduces the chromatic aliasing occurring at the lower frequencies as a result of sub-sampling. Accordingly, chromatic aliasing frequencies that are originally so high that they fold over at the Nyquist frequency to very low frequencies, that would otherwise be highly visible, are reduced.
  • [0054]
    The visual model 76 may take a different form than the known model used in the Betrisey approach. In known models, such as Betrisey, the visual model is a difference measure where two images are input and the output is an image indicating where visual differences occur. In the Betrisey approach, this image of visible differences is integrated in a squared form to arrive at a single number measure. These known models are described in X. Zhang and B Wandell (1996), “A spatial extension of CIELAB for digital color image reproduction, SID Symposium Digest 731-734; C. Betrisey, et al. (2000), “Displaced filtering for patterned displays,” SID Symposium Digest, 296-299; and S. Daly (1993), “Visible Differences Predictor,” Ch. 14 of Digital Images and Human Vision, ed. by A. B. Watson, MIT Press. These references are incorporated herein by reference.
  • [0055]
    In one embodiment, the visual model 76 removes or otherwise reduces the visibility of image content that is generally not visible or otherwise of limited visibility to the eye. Consequently, the visual model does not necessarily need to compute the visible difference between images, but rather may act on a single image. In alternative embodiments, the embodiments may be extended to operate upon multiple images, which achieving similar results in luminance resolution and the reduction of chromatic aliasing. One way to achieve this result is to filter the image by the appropriate CSFs and core by the threshold. In FIG. 8, the visual model 76 is shown in generic form.
  • [0056]
    In reference to FIG. 9, the system may be used in conjunction with standard pre-process methods 84, such as the more traditional techniques of hinting and low-pass filtering. Once standard pre-processing methods 84 are performed, the image is treated in the same manner as those without pre-process techniques. That is, the high-resolution image 70 is pre-processed 84 followed by sampling in a sub-pixel sampling simulation 72 to simulate the error caused by sub-pixel sampling. The error may be isolated by subtracting 74 the simulation 72 from the original image. A visual model 76, then reduces non-detectable information from the error image creating a modified error image which represents the visible error. The compensated image is then obtained by adding to the original image 70 the visible error that will be reduced during actual sub-pixel sampling 80. The compensated image 82 is sampled using a sub-pixel sampling process 80 wherein the subtracted visible error is reduced, or otherwise removed, as a result of the sub-pixel sampling process.
  • [0057]
    The visual model 76 may be used in conjunction with different embodiments described herein. Referring to FIG. 10, image 70 may be pre-processed 84 if desired by a user or processed directly without pre-processing. The image 70 is processed by the sub-pixel sampling simulation 72 to determine the error associated with sub-pixel sampling. The simulated image is then subtracted 74 from original image 70 to produce an error image which is processed through the visual model 76. In this embodiment, the visual model 76 comprises a conversion 90 from RGB to LAB. This conversion 90 results in an image expressed in three channels which isolates (to some degree) the luminance characteristics from chromatic characteristics. While several color models may be used, the CIELAB model is exemplary and an equivalent model is preferred in this embodiment. Another embodiment using linear Y, R-Y, and B-Y signals may likewise be used. In many cases, a conversion to a color space (or otherwise calculations) that enhances the luminance information in one or more channels in relation to the chromatic information, is desirable.
  • [0058]
    Once the simulated error image has been converted, the luminance channel 92 and the chrominance channels 94 and 96 are filtered to remove the generally non-visible errors from the error image. Preferably, these filtering operations comprise filtering and a spatial coring operation to remove localized frequencies whose amplitudes are too small to be effectively observed. Different filters may be used for each channel while some channels may not be filtered as desired for specific applications. Typically, the luminance channel 92 and each chrominance channel 94 and 96 are filtered using different filters. This LAB visible error image is subsequently re-converted 100 back to a RGB format visible error image 101. The RGB visible error image 101 is then subtracted from 78 the original image 70 to form a compensated image 82 which compensates for errors introduced through sub-pixel sampling. This compensated image 82 is then sampled using sub-pixel sampling 80 wherein the added visible error compensation 101 is canceled in the sampling process yielding a lower-resolution image with fewer chromatic artifacts than one created through simple sub-pixel sampling alone.
  • [0059]
    In another embodiment, as illustrated in FIG. 11, edge effects or masking as well as frequency effects are treated. Generally, the image processing is performed on a high-resolution image such as RGB high-resolution image 110, if desired. Pre-processing 112 may be performed, if desired.
  • [0060]
    High-resolution image 110 is processed by a sub-pixel sampling simulation 114 which isolates the error introduced during sub-pixel sampling by performing the sampling simulation and converting the sampled image to its original resolution for comparison to the original, and subsequently primarily processed as previously described. Within the visual model 76, the error image, in a RGB or similar format is converted 120 to a LAB or similar format thereby segregating luminance data from chrominance data. After conversion to a luminance-enhanced format, such as LAB, the channels of luminance 122 and chrominance 124 and 126 are filtered.
  • [0061]
    After filtering 122, 124 and 126, the effects of masking, particularly the masking of chrominance by luminance, may be taken into account. The masking signal is preferably obtained from the source image 110 content rather than the error image. The source image 110 is converted 128 to a luminance-segregated format such as LAB from which the luminance data is extracted 130. In some embodiments, only the luminance channel 136 is masked. However chromatic channels 134 and 132 may also be masked, if desired. Masking is preferably performed as a pixel-wise comparison to account for edge effects. Masking is dependant on local contrast which is proportional to subtracting the mean of the entire L image from the L image then using the absolute value. A higher contrast signal level in L at a given position should result in more masking of the L, R/G, and B/Y signals at the same position. The masking is simulated by dividing these signals by the mask signal output from step 130, and then coring. Coring is a process by which a signal's value is changed to zero when the absolute value of the signal amplitude becomes less than a given threshold value.
  • [0062]
    Once masking has taken place, the LAB channels may be converted 140 back to the original image format, for example RGB. The resulting image represents the visible error 142 associated with sub-pixel sampling.
  • [0063]
    This resulting error image 142 is subsequently subtracted from the original high-resolution image 144 to create a compensated image 146 in which a correction is introduced which is substantially similar, but opposite to the error introduced during sub-pixel sampling. This compensated image 146, when sampled 148 results in a display image 150 which contains fewer errors than a directly sampled image without error correction. This is due to the reduction of the sampling errors by the visible error 142 introduced 144 before sampling 148.
  • [0064]
    The embodiment, as illustrated in FIG. 11, can only partially model the masking effect since the actual visual masking process primarily uses signals whose frequency content are mask frequency and whose spatial extent and position are similar. For images consisting solely of edges and lines, a 1/f-power spectra may be assumed. Thus at any given frequency and orientation, the signal content at higher frequencies with the same orientation will be less. Thus this approach generally overestimates masking, but since that will result in more error content in the error image, the net effect is that more chromatic aliasing is removed than necessary. This results in less luminance sharpness, but it will still be more than techniques that do not use masking aspects.
  • [0065]
    Referring to FIG. 12, another embodiment employs a more complete visual model 151 capable of predicting masking more accurately by the use of multiple frequency channels. Although only four channels are shown, their actual number may be greater or lesser, and they are typically both bandpass and limited in spatial orientation. Example channels are described in S. Daly (1993), “Visible Differences Predictor,” Ch. 14 of Digital Images and Human Vision, ed. By A. B. Watson, MIT Press; and J. Lubin (1995), “A Visual Discrimination Model for Imaging System Design and Evaluation,” Ch. 10 of Vision Models for Target Detection and Recognition, ed. by E. Peli, World Scientific Press; incorporated herein by reference.
  • [0066]
    A high-resolution image 110 may be optionally pre-processed 112 before sub-pixel sampling simulation 114. As in previously described embodiments, sub-pixel sampling simulation 114 is used to determine the error introduced by sub-pixel sampling. This error image may be isolated 116 from the simulation through direct comparison of the “post-processed” image to the original image 110 at the original image resolution. Generally, the lower resolution “post-processed” image is increased in resolution for comparative purposes. Once this error image 118 is obtained, the error image 118 may be processed in a visual model 151 of this embodiment.
  • [0067]
    As in other embodiments, the error image 118 is preferably converted from RGB or similar formats to a luminance-segregated format such as LAB 152. Using this type of format, the luminance and chrominance channels are further divided into frequency ranges using filter bank decomposition 154, 156 and 158. Each frequency range within each channel is then filtered using band scaling 160, 162 and 164.
  • [0068]
    Edge effects are also accounted for by converting the original source image to a luminance-segregated format such as LAB 166 followed by filter bank decomposition of the luminance channel 168 from the original image 110. Generally, the segregated chrominance channels 165 are not used in the masking process. Following filter bank decomposition 168, the frequency ranges are filtered via band scaling or similar procedures as performed for the main error image channels 160, 162 and 164. These signals created through luminance channel band scaling 170 may be used for masking the various luminance and chrominance channels 172, 174 and 176. The masking computation is similar to that described in conjunction with FIG. 11. However, in the computation of FIG. 12, the masking signal from a specific frequency band preferably only affects the corresponding frequency band of the error image.
  • [0069]
    Once masking has been completed for each frequency band of each channel, the resultant LAB signals may then be converted back to the original image format such as RGB 180. This RGB or similar file 180 represents the visible error introduced during sub-pixel sampling. The visible error 180 is subsequently subtracted (or otherwise) 188 from with the original high-resolution source file 110 thereby creating a compensated image 182.
  • [0070]
    The compensated image 182, when sampled 184 results in a display image which contains fewer errors than a directly sampled image without error correction. This is due to the reduction of the sampling errors by the visible error introduced before sampling. This embodiment uses a visual model with multi-channel capability that provides for masking of chroma by luminance.
  • [0071]
    Referring to FIG. 13, wherein a high-resolution grey scale image, such as RGB high-resolution image 170, is modified. Unlike some known methods, the process may be carried in domains other than the RGB domain. The YCrCb color domain may also be used, wherein the luminance components (Red-Green and Blue-Yellow) are separated. Other domains that are approximations to the visual systems opponent color channels are desirable. Examples include CIELAB, YUV, and Y R-Y B-Y. The chromatic components are subjected to modification that leads to attenuation of low chromatic frequencies in comparison to the high chromatic frequencies, eventually yielding a better sub-pixel sampled image that has fewer visible chromatic artifacts.
  • [0072]
    As FIG. 13 illustrates, the initial high-resolution image 170 in RGB format includes R 172, G 174 and B 176 data. These individual data sets may then be passed through low pass filters (LPF) 178, 180 and 182. This filtering essentially removes high frequency luminance and chromatic components that may alias in spite of the sub-pixel sub-sampling process. A bypass 171 of the RGB low-pass filtering steps may be used. Different filters may be used for different color layers. Generally some luminance information is allowed to exist which is greater than the displayed pixel Nyquist; that is, the luminance frequencies within the advantage region.
  • [0073]
    The filtered RGB image is then subjected to sub-pixel sub-sampling 186 that results in a 3× down sampled image while retaining horizontal luminance resolution beyond the down sampled pixel Nyquist frequency. Unfortunately, the sub-pixel sampling introduces chromatic artifacts, some of which may be visible as they occur at a sufficiently low spatial frequency. The goal is to reduce those occurring at frequencies low enough to be visible (i.e., falling within the chromatic CSF passband) while retaining the aforementioned horizontal luminance resolution. The RGB image is modified 188 into Y 190, Cb 192, and Cr 194 components. Other color domains and chromatic channels may also be used. In this particular embodiment, the Cb 192 and Cr 194 components are then high-pass filtered 196. When this filtering is performed, the low frequencies in Cb and Cr, that developed during sub-pixel sub-sampling, are removed by the high-pass filtering. High-pass filtering 196 generally is achieved through low-frequency attenuation rather than high-frequency enhancement. The filtered Cb and Cr components and the unfiltered Y component 190 are jointly converted 200 back to RGB to yield the final low-resolution image 202 that is ⅓ the original image's dimension with significantly reduced chromatic artifacts and significantly increased horizontal luminance resolution with ordinary sub-sampling.
  • [0074]
    Referring to FIG. 14, the retained signals relative to the luminance CSFs 210 and chromatic CSFs 212 are shown. The chromatic signals 214 are preserved in the high-pass region, which are undetectable to the eye. The HPF chromatic signal 214 is the chromatic aliasing that carries valid high resolution luminance information 216.
  • [0075]
    The high-pass filtering may be performed via an unsharp mask. The unsharp mask may use a low-pass kernel. Typically, the incoming signal is processed with the low-pass kernel yielding a low-pass version of the signal. This low-pass version (or an amplitude scaled version) is subsequently subtracted from incoming signal while preserving the signal's mean value resulting in a high pass image.
  • [0076]
    One embodiment may use high-pass filters which are equivalent to the compliment of the chromatic CSFs. These CSFs may be mapped from the domain of cy/deg (where they are modeled) to the digital domain of cy/pix. The actual mapping process takes into account the viewing distance, and allows for customization for different applications, having particular display resolutions in pixels/mm and different expected or intended viewing distances. Also, these filters may take into account the particular luminance-enhanced color space being used. As a result, chromatic artifacts will be reduced when viewed no closer than the designed viewing distance. However, the luminance resolution will be improved.
  • [0077]
    [0077]FIG. 15 shows the signals retained relative to the luminance CSF 430 and chromance CSF 432. The chromance signals preserved include the high-pass region 434 (result of a achromatic processing, see FIG. 16), which is undetectable to the visual system as well as the low-pass region 436 (result of chromatic processing, see FIG. 16), which contains the useful low pass chromatic content of the original image. The HPF chromatic signal 434 is the chromance aliasing that carries valid high resolution luminance information. FIG. 15 shows no overlap between these two chromatic signals, but depending on the actual filters used, overlap may exist. Other embodiments may include the use of filters that allow for overlap of the high-pass 434 and low-pass 436 chromatic signals shown in FIG. 15. Overlap can allow for more chromatic bandwidth at the expense of chromance aliasing.
  • [0078]
    Referring to FIG. 16, another processing technique, similar in nature to the other processing techniques is shown. An input image 500, such as a RBG image, may be pre-processed 502 using any suitable technique. The input image 500 may be a gamma corrected image, if desired. The gamma correction may be inverted 504, if desired. The gamma inverted image 504 is converted to a luminance enhanced color space 506, such as a LAB color space. The luminance channel 508 is then converted to a RGB color space 510. In effect, the conversion to RGB color space 510 creates an image that is composed of luminance information or otherwise all the values for the red, green, and blue components of the relevant pixels each have the same value, namely, that of the luminance value of the pixel. In other words, for each relevant pixel the RGB values of that pixel's sub-pixels are replaced by the corresponding luminance value.
  • [0079]
    The RGB image at the output of block 510 may be filtered in a suitable manner (such as a low-pass filter) and sub-pixel sub-sampled 512, such as shown in FIG. 2, for example. The result of sub-pixel sub-sampling 512 is a spatial displacement of the luminance information as illustrated in FIG. 2, which is the result of a 3:1 down sampling ratio, but other ratios may be used depending upon the sub-pixel sub-sampling process and the prefiltering. The sub-pixel sub-sampling process of the luminance information creates spurious color information because the different color fields alias differently. The RGB sub-sampled image 514 is converted to a luminance enhanced color space 516. The color information created as a result of the sub-pixel sub-sampling process 512 includes chromatic aliasing. The chromatic channels A and B are high pass filtered by filters 518 and 520, respectively. Filters 518 and 520 reduce the low frequency chromatic information (or with respect to high frequency chromatic information) resulting from the sub-sampling of the luminance information. The luminance channel and the chromatic A and B channels are converted to RGB space 522, gamma corrected 524, and converted to LAB color space 526. The primary result of the achromatic processing 528 is to sub-pixel sub-sample the luminance information to achieve high luminance bandwidth while reducing the resulting generally visible chromatic aliasing (lower chromatic frequencies) that results from the sub-pixel sub-sampling of the luminance information. The generally non-visible chromatic aliasing (higher chromatic frequencies) may be maintained because it carries with it high resolution luminance information that may be observed by the viewer. It is noted that the luminance CSF has a substantially higher cutoff frequency than the chromatic CSF.
  • [0080]
    In the case that the input image is a color image the original chromatic content may be processed in a separate manner, namely, the chromatic processing branch of FIG. 16. The pre-processed image 502 may be converted to a luminance enhanced color space 530, such as LAB. The color channels A 532 and B 534 may be filtered by a corresponding low pass filter 536 and 538 in order to reduce potential aliasing. The filtered color channels A 540 and B 542 are sub-sampled 544 in an ordinary manner. The ordinarily sub-sampled channels 546 and 548 generally include the chromatic information for the image.
  • [0081]
    The luminance channel 550 generally includes the luminance information for the image at a bandwidth commensurate with the pixel sampling rate. The high frequency chromatic channels 552 and 554 that are aliased contain high resolution luminance data. These may be added to the color channels A 546 and B 548 (or otherwise combined in some manner) which contain the sub-sampled chromance from the original image. The result of these operations is a color display with luminance resolution that exceeds that normally associated with the pixel sampling rate. The resulting image is converted from LAB to RGB color space.
  • [0082]
    It is to be understood that any sub-pixel arrangement may likewise by used, such as those illustrated in FIGS. 17 and 18. The techniques described herein are applicable to horizontal one-dimensional filtering, vertical one-dimensional filtering, or two-dimensional filtering. In addition the filtering in 1D or 2D may be performed on an axis that is not aligned with the pixels or sub-pixels. Further, any post processing that may be desired may be performed prior to re-sampling. Furthermore, the chromatic aliasing may be reduced by using a suitable matrix of pre-filters in a manner similar to Betrisey, et al. Furthermore, the sub-pixel sub-sampling may be replaced with an ordinary sub-sampling operation and the phase shift(s) of the color planes incorporated into the pre-filters.
  • [0083]
    In the case of typical R, G, B sub-pixels, many designers tend to ignore the luminance contribution of B because it is typically less than 15%. In this case designers tend to primarily use R and G contributions in the algorithm design. However, the present inventors came to the realization that the resulting luminance pattern has non-uniform samples, namely, red luminance, green luminance, no luminance, etc. The existing systems fail to take into account this non-uniformity of the display. Moreover, the pattern shown in FIG. 18 has non-uniform luminance samples due to the red and blue sub-pixels, this is because the centroids of the sub-pixels are off center. To achieve improved re-sampling, especially in the case that the luminance and chromatic aspects are sampled differently, the processing may take into account the non-uniform sampling in a manner that reduces artifacts, such as chromatic artifacts, to less than it would have been had the non-uniform sampling not been considered.

Claims (38)

    What is claimed is:
  1. 1. A method for re-sampling an image having chromatic information and luminance information comprising the steps of:
    (a) re-sampling said luminance information using a first re-sampling process and attenuating at least a portion of lower frequency chromatic information with respect to at least a portion of higher frequency chromatic information resulting from said re-sampling of said luminance information;
    (b) re-sampling said chromatic information of said image using a second re-sampling process, at least one of:
    (i) re-sampling of said luminance information is different than said re-sampling of said chromatic information; and
    (ii) said second process processes pixels of said image in a manner different than said first process;
    (c) combining said re-sampled luminance information, said re-sampled chromatic information, and at least a portion of said higher frequency chromatic information into a re-sampled image.
  2. 2. The method of claim 1 wherein said re-sampling of said luminance includes re-sampling.
  3. 3. The method of claim 1 wherein said attenuating is using a high pass filter.
  4. 4. The method of claim 1 wherein said re-sampling of said luminance information results in two chromatic channels, where each of said chromatic channels is attenuated in a different manner.
  5. 5. The method of claim 1 wherein said re-sampling of said luminance information is in accordance with a model based upon the human visual system.
  6. 6. The method of claim 1 wherein said re-sampling of said chromatic information includes re-sampling.
  7. 7. The method of claim 1 wherein said re-sampling of said luminance information of said image is performed in such a manner that chromatic aliasing is reduced from what it would have been had said re-sampling of said luminance information been re-sampled in the same manner as said re-sampling of said chromatic information.
  8. 8. The method of claim 1 wherein said re-sampling of said luminance information is performed on a luminance portion of said image free from substantial re-sampling of chromatic information of said image, while said re-sampling of said chromatic information is performed on a chromatic portion of said image free from substantial re-sampling of luminance information of said image.
  9. 9. A method for re-sampling an image comprising the steps of:
    (a) re-sampling luminance information of said image, wherein said luminance information is at least 60% of the luminance of said image; and
    (b) attenuating at least a portion of lower frequency chromatic information with respect to at least a portion of higher frequency chromatic information resulting from said re-sampling of said luminance information.
  10. 10. The method of claim 9 wherein said re-sampling of said luminance includes pixel re-sampling.
  11. 11. The method of claim 9 wherein said attenuating is using a high pass filter.
  12. 12. The method of claim 9 wherein said re-sampling of said luminance information results in two chromatic channels, where each of said chromatic channels is attenuated in a different manner.
  13. 13. A method for re-sampling an image comprising a plurality of channels, wherein a first one of said channels has a luminance component comprising at least 60% of the luminance of said image, wherein in a second one of said channels has a color component;
    (a) re-sampling said first channel of said image;
    (b) attenuating at least a portion of lower frequency chromatic information with respect to at least a portion of higher frequency chromatic information resulting from said re-sampling of said first channel of said image; and
    (c) re-sampling said second channel of said image.
  14. 14. The method of claim 13 wherein said luminance component comprises at least 70% of the luminance of said image.
  15. 15. The method of claim 13 wherein said luminance component comprises at least 80% of the luminance of said image.
  16. 16. The method of claim 13 wherein said luminance component comprises at least 90% of the luminance of said image.
  17. 17. The method of claim 13 wherein said plurality of channels are color difference channels.
  18. 18. A method for re-sampling an image comprising the steps of:
    (a) providing a channel of said image comprising at least 60% of the luminance of said image;
    (b) attenuating at least a portion of the lower frequency luminance information with respect to at least a portion of the higher frequency luminance information of said channel; and
    (c) re-sampling luminance information of said image.
  19. 19. The method of claim 18 further comprising attenuating at least a portion of lower frequency chromatic information with respect to at least a portion of higher frequency chromatic information resulting from said re-sampling of said luminance information.
  20. 20. The method of claim 18 wherein said luminance component comprises at least 70% of the luminance of said image.
  21. 21. The method of claim 18 wherein said luminance component comprises at least 80% of the luminance of said image.
  22. 22. The method of claim 18 wherein said luminance component comprises at least 90% of the luminance of said image.
  23. 23. The method of claim 18 wherein said luminance component comprises at least 95% of the luminance of said image.
  24. 24. A method for re-sampling an image having chromatic information and luminance information comprising the steps of:
    (a) re-sampling said luminance information using a first re-sampling process;
    (b) re-sampling said chromatic information of said image using a second re-sampling process, at least one of:
    (i) re-sampling of said luminance information is different than said re-sampling of said chromatic information; and
    (ii) said second process processes pixels of said image in a manner different than said first process;
    (c) attenuating at least a portion of lower frequency chromatic information with respect to at least a portion of higher frequency chromatic information that at least one of wold result from and that results from said re-sampling of said luminance information;
    (d) combining said re-sampled luminance information, said re-sampled chromatic information, and at least a portion of said higher frequency chromatic information into a re-sampled image.
  25. 25. The method of claim 24 wherein said re-sampling of said luminance information is performed prior to said re-sampling of said luminance information.
  26. 26. The method of claim 24 wherein said attenuating is using a high pass filter.
  27. 27. The method of claim 24 wherein said re-sampling of said luminance information results in two chromatic channels, where each of said chromatic channels is attenuated in a different manner.
  28. 28. The method of claim 24 wherein said re-sampling of said chromatic information includes pixel re-sampling.
  29. 29. The method of claim 24 wherein said re-sampling of said luminance information of said image is performed in such a manner that chromatic aliasing is reduced from what it would have been had said re-sampling of said luminance information been re-sampled in the same manner as said re-sampling of said chromatic information.
  30. 30. The method of claim 24 wherein said re-sampling of said luminance information is performed on a luminance portion of said image free from substantial re-sampling of chromatic information of said image, while said re-sampling of said chromatic information is performed on a chromatic portion of said image free from substantial re-sampling of luminance information of said image.
  31. 31. A method for re-sampling an image comprising the steps of:
    (a) re-sampling said image;
    (b) filtering said image in a manner such that the luminous information has a non-uniform sampling rate;
    (c) modifying said image by taking into account said non-uniform sampling rate in such a manner that reduces the chromatic artifacts of said image to less than it would have been had said non-uniform sampling been taken into account.
  32. 32. The method of claim 31 wherein said image has a luminance non-uniform sampling rate in the horizontal direction.
  33. 33. The method of claim 31 wherein said image has a luminance non-uniform sampling rate in the vertical direction.
  34. 34. The method of claim 31 wherein said image has a luminance non-uniform sampling rate in a diagonal direction.
  35. 35. The method of claim 31 wherein said filtering is performed prior to said re-sampling.
  36. 36. The method of claim 31 wherein said modifying is performed prior to said filtering.
  37. 37. The method of claim 31 wherein said modifying is performed prior to said re-sampling.
  38. 38. The method of claim 31 wherein said filtering include a high pass filter of chromatic information.
US10447186 2000-06-12 2003-05-27 System for improving display resolution Active 2021-12-31 US7110012B2 (en)

Priority Applications (6)

Application Number Priority Date Filing Date Title
US21102000 true 2000-06-12 2000-06-12
US09735425 US6807319B2 (en) 2000-06-12 2000-12-12 Methods and systems for improving display resolution in achromatic images using sub-pixel sampling and visual error filtering
US09735424 US6608632B2 (en) 2000-06-12 2000-12-12 Methods and systems for improving display resolution in images using sub-pixel sampling and visual error filtering
US09735454 US6775420B2 (en) 2000-06-12 2000-12-12 Methods and systems for improving display resolution using sub-pixel sampling and visual error compensation
US46943203 true 2003-05-09 2003-05-09
US10447186 US7110012B2 (en) 2000-06-12 2003-05-27 System for improving display resolution

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US10447186 US7110012B2 (en) 2000-06-12 2003-05-27 System for improving display resolution
JP2004129090A JP4688432B2 (en) 2003-05-09 2004-04-23 System for improving the display resolution
KR20040029260A KR100636658B1 (en) 2003-05-09 2004-04-27 System for improving display resolution
EP20040252436 EP1484743A3 (en) 2003-05-09 2004-04-27 System for improving display resolution
US10890871 US7035476B2 (en) 2000-06-12 2004-07-12 Methods and systems for improving display resolution using sub-pixel sampling and visual error compensation

Related Parent Applications (3)

Application Number Title Priority Date Filing Date
US09735425 Continuation US6807319B2 (en) 2000-06-12 2000-12-12 Methods and systems for improving display resolution in achromatic images using sub-pixel sampling and visual error filtering
US09735424 Continuation US6608632B2 (en) 2000-06-12 2000-12-12 Methods and systems for improving display resolution in images using sub-pixel sampling and visual error filtering
US09735454 Continuation US6775420B2 (en) 2000-06-12 2000-12-12 Methods and systems for improving display resolution using sub-pixel sampling and visual error compensation

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US10890871 Continuation US7035476B2 (en) 2000-06-12 2004-07-12 Methods and systems for improving display resolution using sub-pixel sampling and visual error compensation

Publications (2)

Publication Number Publication Date
US20040061710A1 true true US20040061710A1 (en) 2004-04-01
US7110012B2 US7110012B2 (en) 2006-09-19

Family

ID=33162126

Family Applications (1)

Application Number Title Priority Date Filing Date
US10447186 Active 2021-12-31 US7110012B2 (en) 2000-06-12 2003-05-27 System for improving display resolution

Country Status (4)

Country Link
US (1) US7110012B2 (en)
EP (1) EP1484743A3 (en)
JP (1) JP4688432B2 (en)
KR (1) KR100636658B1 (en)

Cited By (41)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030103058A1 (en) * 2001-05-09 2003-06-05 Candice Hellen Brown Elliott Methods and systems for sub-pixel rendering with gamma adjustment
US20030117423A1 (en) * 2001-12-14 2003-06-26 Brown Elliott Candice Hellen Color flat panel display sub-pixel arrangements and layouts with reduced blue luminance well visibility
US20030128225A1 (en) * 2002-01-07 2003-07-10 Credelle Thomas Lloyd Color flat panel display sub-pixel arrangements and layouts for sub-pixel rendering with increased modulation transfer function response
US20040080479A1 (en) * 2002-10-22 2004-04-29 Credelle Thomas Lioyd Sub-pixel arrangements for striped displays and methods and systems for sub-pixel rendering same
US20040113922A1 (en) * 2002-08-24 2004-06-17 Samsung Electronics Co., Ltd. Method and apparatus for rendering color image on delta-structured displays
US20040174380A1 (en) * 2003-03-04 2004-09-09 Credelle Thomas Lloyd Systems and methods for motion adaptive filtering
US20040196297A1 (en) * 2003-04-07 2004-10-07 Elliott Candice Hellen Brown Image data set with embedded pre-subpixel rendered image
US20040233339A1 (en) * 2003-05-20 2004-11-25 Elliott Candice Hellen Brown Projector systems with reduced flicker
US20040233308A1 (en) * 2003-05-20 2004-11-25 Elliott Candice Hellen Brown Image capture device and camera
US20040232844A1 (en) * 2003-05-20 2004-11-25 Brown Elliott Candice Hellen Subpixel rendering for cathode ray tube devices
US20040246278A1 (en) * 2003-06-06 2004-12-09 Elliott Candice Hellen Brown System and method for compensating for visual effects upon panels having fixed pattern noise with reduced quantization error
US20040246279A1 (en) * 2003-06-06 2004-12-09 Credelle Thomas Lloyd Dot inversion on novel display panel layouts with extra drivers
US20040246404A1 (en) * 2003-06-06 2004-12-09 Elliott Candice Hellen Brown Liquid crystal display backplane layouts and addressing for non-standard subpixel arrangements
US20040246381A1 (en) * 2003-06-06 2004-12-09 Credelle Thomas Lloyd System and method of performing dot inversion with standard drivers and backplane on novel display panel layouts
US20050068335A1 (en) * 2003-09-26 2005-03-31 Tretter Daniel R. Generating and displaying spatially offset sub-frames
US20050083277A1 (en) * 2003-06-06 2005-04-21 Credelle Thomas L. Image degradation correction in novel liquid crystal displays with split blue subpixels
US20050099540A1 (en) * 2003-10-28 2005-05-12 Elliott Candice H.B. Display system having improved multiple modes for displaying image data from multiple input source formats
US20050104908A1 (en) * 2001-05-09 2005-05-19 Clairvoyante Laboratories, Inc. Color display pixel arrangements and addressing means
US20050225574A1 (en) * 2004-04-09 2005-10-13 Clairvoyante, Inc Novel subpixel layouts and arrangements for high brightness displays
US20050225563A1 (en) * 2004-04-09 2005-10-13 Clairvoyante, Inc Subpixel rendering filters for high brightness subpixel layouts
US20050276502A1 (en) * 2004-06-10 2005-12-15 Clairvoyante, Inc. Increasing gamma accuracy in quantized systems
US20060284872A1 (en) * 2005-06-15 2006-12-21 Clairvoyante, Inc Improved Bichromatic Display
US20070046689A1 (en) * 1999-03-24 2007-03-01 Avix Inc. Method and apparatus for displaying bitmap multi-color image data on dot matrix-type display screen on which three primary color lamps are dispersedly arrayed
US20070045549A1 (en) * 2005-08-30 2007-03-01 Chun-Fu Wang Method for Adjusting the Visual Qualities of Images Displayed on a Monitor and Related Monitor
US20070052887A1 (en) * 2002-09-13 2007-03-08 Clairvoyante, Inc Four color arrangements of emitters for subpixel rendering
US20070064020A1 (en) * 2002-01-07 2007-03-22 Clairvoyante, Inc. Color flat panel display sub-pixel rendering and driver configuration for sub-pixel arrangements with split sub-pixels
US20070071352A1 (en) * 2001-05-09 2007-03-29 Clairvoyante, Inc Conversion of a sub-pixel format data to another sub-pixel data format
US20080049047A1 (en) * 2006-08-28 2008-02-28 Clairvoyante, Inc Subpixel layouts for high brightness displays and systems
US20080094419A1 (en) * 2006-10-24 2008-04-24 Leigh Stan E Generating and displaying spatially offset sub-frames
US20080111771A1 (en) * 2006-11-09 2008-05-15 Miller Michael E Passive matrix thin-film electro-luminescent display
US20090080805A1 (en) * 2004-10-29 2009-03-26 Tokyo Institute Of Technology Fast Method of Super-Resolution Processing
US20090237530A1 (en) * 2008-03-20 2009-09-24 Ilia Ovsiannikov Methods and apparatuses for sharpening images
US8018476B2 (en) 2006-08-28 2011-09-13 Samsung Electronics Co., Ltd. Subpixel layouts for high brightness displays and systems
US8022969B2 (en) 2001-05-09 2011-09-20 Samsung Electronics Co., Ltd. Rotatable display with sub-pixel rendering
US8035599B2 (en) 2003-06-06 2011-10-11 Samsung Electronics Co., Ltd. Display panel having crossover connections effecting dot inversion
US20110279493A1 (en) * 1997-09-13 2011-11-17 Gia Chuong Phan Display and weighted dot rendering method
US8134583B2 (en) 2002-01-07 2012-03-13 Samsung Electronics Co., Ltd. To color flat panel display sub-pixel arrangements and layouts for sub-pixel rendering with split blue sub-pixels
US8405692B2 (en) 2001-12-14 2013-03-26 Samsung Display Co., Ltd. Color flat panel display arrangements and layouts with reduced blue luminance well visibility
US20130141480A1 (en) * 2011-12-02 2013-06-06 Industrial Technology Research Institute System and method for improving visual effect of a display device
US20170039990A1 (en) * 2015-08-05 2017-02-09 Boe Technology Group Co., Ltd. Pixel array, display device and driving method thereof, and driving device
US20170103566A1 (en) * 2015-10-12 2017-04-13 Samsung Electronics Co., Ltd. Texture processing method and unit

Families Citing this family (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050151752A1 (en) * 1997-09-13 2005-07-14 Vp Assets Limited Display and weighted dot rendering method
US7283142B2 (en) * 2000-07-28 2007-10-16 Clairvoyante, Inc. Color display having horizontal sub-pixel arrangements and layouts
US7274383B1 (en) 2000-07-28 2007-09-25 Clairvoyante, Inc Arrangement of color pixels for full color imaging devices with simplified addressing
JP4813787B2 (en) * 2003-10-17 2011-11-09 パナソニック株式会社 Image processing apparatus and method
US7463272B2 (en) * 2004-01-30 2008-12-09 Hewlett-Packard Development Company, L.P. Generating and displaying spatially offset sub-frames
JP4635629B2 (en) * 2004-03-30 2011-02-23 日本ビクター株式会社 Sampling rate conversion device and an image signal processing method
JP4736456B2 (en) * 2005-02-15 2011-07-27 株式会社日立製作所 Scanning line interpolation apparatus, the image display device, a video signal processing device
KR101265956B1 (en) 2007-11-02 2013-05-22 삼성전자주식회사 Image restoration system and method of the block-based
KR101481668B1 (en) * 2008-07-08 2015-01-13 엘지디스플레이 주식회사 Liquid crystal display device and method for driving the same
US8422813B2 (en) * 2009-03-13 2013-04-16 Asustek Computer Inc. Image processing device and image processing method
US9196199B2 (en) 2013-02-12 2015-11-24 Pixtronix, Inc. Display having staggered display element arrangement

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5528740A (en) * 1993-02-25 1996-06-18 Document Technologies, Inc. Conversion of higher resolution images for display on a lower-resolution display device
US6608632B2 (en) * 2000-06-12 2003-08-19 Sharp Laboratories Of America, Inc. Methods and systems for improving display resolution in images using sub-pixel sampling and visual error filtering
US6775420B2 (en) * 2000-06-12 2004-08-10 Sharp Laboratories Of America, Inc. Methods and systems for improving display resolution using sub-pixel sampling and visual error compensation
US6807319B2 (en) * 2000-06-12 2004-10-19 Sharp Laboratories Of America, Inc. Methods and systems for improving display resolution in achromatic images using sub-pixel sampling and visual error filtering

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000078604A (en) 1998-09-02 2000-03-14 Victor Co Of Japan Ltd Color band improvement circuit
JP3565327B2 (en) * 1999-08-05 2004-09-15 シャープ株式会社 Display device
EP1350221A2 (en) 2000-12-12 2003-10-08 Sharp Corporation Methods and systems for improving display resolution in images using sub-pixel sampling and visual error filtering
JP3565328B2 (en) * 2000-06-13 2004-09-15 シャープ株式会社 Display device and the defective dot compensation method
JP4807866B2 (en) * 2000-12-15 2011-11-02 シャープ株式会社 Color reproduction processing switching device and readable recording medium
JP3879431B2 (en) 2001-04-16 2007-02-14 三菱電機株式会社 Scanning line converting apparatus
US7221381B2 (en) * 2001-05-09 2007-05-22 Clairvoyante, Inc Methods and systems for sub-pixel rendering with gamma adjustment
JP2003006630A (en) * 2001-06-19 2003-01-10 Fujitsu Ltd Device and method for displaying color image
US20040239813A1 (en) 2001-10-19 2004-12-02 Klompenhouwer Michiel Adriaanszoon Method of and display processing unit for displaying a colour image and a display apparatus comprising such a display processing unit

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5528740A (en) * 1993-02-25 1996-06-18 Document Technologies, Inc. Conversion of higher resolution images for display on a lower-resolution display device
US6608632B2 (en) * 2000-06-12 2003-08-19 Sharp Laboratories Of America, Inc. Methods and systems for improving display resolution in images using sub-pixel sampling and visual error filtering
US6775420B2 (en) * 2000-06-12 2004-08-10 Sharp Laboratories Of America, Inc. Methods and systems for improving display resolution using sub-pixel sampling and visual error compensation
US6807319B2 (en) * 2000-06-12 2004-10-19 Sharp Laboratories Of America, Inc. Methods and systems for improving display resolution in achromatic images using sub-pixel sampling and visual error filtering
US20040264798A1 (en) * 2000-06-12 2004-12-30 Daly Scott J. Methods and systems for improving display resolution using sub-pixel sampling and visual error compensation

Cited By (94)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110279493A1 (en) * 1997-09-13 2011-11-17 Gia Chuong Phan Display and weighted dot rendering method
US8860642B2 (en) * 1997-09-13 2014-10-14 Vp Assets Limited Display and weighted dot rendering method
US20070046689A1 (en) * 1999-03-24 2007-03-01 Avix Inc. Method and apparatus for displaying bitmap multi-color image data on dot matrix-type display screen on which three primary color lamps are dispersedly arrayed
US8085284B2 (en) 1999-03-24 2011-12-27 Avix Inc. Method and apparatus for displaying bitmap multi-color image data on dot matrix-type display screen on which three primary color lamps are dispersedly arrayed
US7187393B1 (en) * 1999-03-24 2007-03-06 Avix Inc. Method and device for displaying bit-map multi-colored image data on dot matrix type display screen on which three-primary-color lamps are dispersedly arrayed
US20070071352A1 (en) * 2001-05-09 2007-03-29 Clairvoyante, Inc Conversion of a sub-pixel format data to another sub-pixel data format
US7911487B2 (en) 2001-05-09 2011-03-22 Samsung Electronics Co., Ltd. Methods and systems for sub-pixel rendering with gamma adjustment
US7864202B2 (en) 2001-05-09 2011-01-04 Samsung Electronics Co., Ltd. Conversion of a sub-pixel format data to another sub-pixel data format
US7688335B2 (en) 2001-05-09 2010-03-30 Samsung Electronics Co., Ltd. Conversion of a sub-pixel format data to another sub-pixel data format
US7689058B2 (en) 2001-05-09 2010-03-30 Samsung Electronics Co., Ltd. Conversion of a sub-pixel format data to another sub-pixel data format
US20100026709A1 (en) * 2001-05-09 2010-02-04 Candice Hellen Brown Elliott Methods and systems for sub-pixel rendering with gamma adjustment
US20030103058A1 (en) * 2001-05-09 2003-06-05 Candice Hellen Brown Elliott Methods and systems for sub-pixel rendering with gamma adjustment
US7916156B2 (en) 2001-05-09 2011-03-29 Samsung Electronics Co., Ltd. Conversion of a sub-pixel format data to another sub-pixel data format
US7889215B2 (en) 2001-05-09 2011-02-15 Samsung Electronics Co., Ltd. Conversion of a sub-pixel format data to another sub-pixel data format
US7755649B2 (en) 2001-05-09 2010-07-13 Samsung Electronics Co., Ltd. Methods and systems for sub-pixel rendering with gamma adjustment
US8022969B2 (en) 2001-05-09 2011-09-20 Samsung Electronics Co., Ltd. Rotatable display with sub-pixel rendering
US8159511B2 (en) 2001-05-09 2012-04-17 Samsung Electronics Co., Ltd. Methods and systems for sub-pixel rendering with gamma adjustment
US20050104908A1 (en) * 2001-05-09 2005-05-19 Clairvoyante Laboratories, Inc. Color display pixel arrangements and addressing means
US8223168B2 (en) 2001-05-09 2012-07-17 Samsung Electronics Co., Ltd. Conversion of a sub-pixel format data
US8830275B2 (en) 2001-05-09 2014-09-09 Samsung Display Co., Ltd. Methods and systems for sub-pixel rendering with gamma adjustment
US20070285442A1 (en) * 2001-05-09 2007-12-13 Clairvoyante, Inc Methods and Systems For Sub-Pixel Rendering With Gamma Adjustment
US20070182756A1 (en) * 2001-05-09 2007-08-09 Clairvoyante, Inc Methods and Systems For Sub-Pixel Rendering With Gamma Adjustment
US7307646B2 (en) 2001-05-09 2007-12-11 Clairvoyante, Inc Color display pixel arrangements and addressing means
US20070153027A1 (en) * 2001-05-09 2007-07-05 Clairvoyante, Inc Conversion of a sub-pixel format data to another sub-pixel data format
US8405692B2 (en) 2001-12-14 2013-03-26 Samsung Display Co., Ltd. Color flat panel display arrangements and layouts with reduced blue luminance well visibility
US20030117423A1 (en) * 2001-12-14 2003-06-26 Brown Elliott Candice Hellen Color flat panel display sub-pixel arrangements and layouts with reduced blue luminance well visibility
US8456496B2 (en) 2002-01-07 2013-06-04 Samsung Display Co., Ltd. Color flat panel display sub-pixel arrangements and layouts for sub-pixel rendering with split blue sub-pixels
US8134583B2 (en) 2002-01-07 2012-03-13 Samsung Electronics Co., Ltd. To color flat panel display sub-pixel arrangements and layouts for sub-pixel rendering with split blue sub-pixels
US20030128225A1 (en) * 2002-01-07 2003-07-10 Credelle Thomas Lloyd Color flat panel display sub-pixel arrangements and layouts for sub-pixel rendering with increased modulation transfer function response
US20070064020A1 (en) * 2002-01-07 2007-03-22 Clairvoyante, Inc. Color flat panel display sub-pixel rendering and driver configuration for sub-pixel arrangements with split sub-pixels
US7755652B2 (en) 2002-01-07 2010-07-13 Samsung Electronics Co., Ltd. Color flat panel display sub-pixel rendering and driver configuration for sub-pixel arrangements with split sub-pixels
US20040113922A1 (en) * 2002-08-24 2004-06-17 Samsung Electronics Co., Ltd. Method and apparatus for rendering color image on delta-structured displays
US7176940B2 (en) * 2002-08-24 2007-02-13 Samsung Electronics Co., Ltd. Method and apparatus for rendering color image on delta-structured displays
US7701476B2 (en) 2002-09-13 2010-04-20 Samsung Electronics Co., Ltd. Four color arrangements of emitters for subpixel rendering
US8294741B2 (en) 2002-09-13 2012-10-23 Samsung Display Co., Ltd. Four color arrangements of emitters for subpixel rendering
US20100164978A1 (en) * 2002-09-13 2010-07-01 Candice Hellen Brown Elliott Four color arrangements of emitters for subpixel rendering
US20070057963A1 (en) * 2002-09-13 2007-03-15 Clairvoyante, Inc. Four color arrangements of emitters for subpixel rendering
US20070052887A1 (en) * 2002-09-13 2007-03-08 Clairvoyante, Inc Four color arrangements of emitters for subpixel rendering
US20040080479A1 (en) * 2002-10-22 2004-04-29 Credelle Thomas Lioyd Sub-pixel arrangements for striped displays and methods and systems for sub-pixel rendering same
US7864194B2 (en) 2003-03-04 2011-01-04 Samsung Electronics Co., Ltd. Systems and methods for motion adaptive filtering
US20040174380A1 (en) * 2003-03-04 2004-09-09 Credelle Thomas Lloyd Systems and methods for motion adaptive filtering
US20070115298A1 (en) * 2003-03-04 2007-05-24 Clairvoyante, Inc Systems and Methods for Motion Adaptive Filtering
US20040196297A1 (en) * 2003-04-07 2004-10-07 Elliott Candice Hellen Brown Image data set with embedded pre-subpixel rendered image
US20080158243A1 (en) * 2003-04-07 2008-07-03 Clairvoyante, Inc Image Data Set With Embedded Pre-Subpixel Rendered Image
US8031205B2 (en) 2003-04-07 2011-10-04 Samsung Electronics Co., Ltd. Image data set with embedded pre-subpixel rendered image
US20040233308A1 (en) * 2003-05-20 2004-11-25 Elliott Candice Hellen Brown Image capture device and camera
US20040232844A1 (en) * 2003-05-20 2004-11-25 Brown Elliott Candice Hellen Subpixel rendering for cathode ray tube devices
US20040233339A1 (en) * 2003-05-20 2004-11-25 Elliott Candice Hellen Brown Projector systems with reduced flicker
US20040246279A1 (en) * 2003-06-06 2004-12-09 Credelle Thomas Lloyd Dot inversion on novel display panel layouts with extra drivers
US20040246381A1 (en) * 2003-06-06 2004-12-09 Credelle Thomas Lloyd System and method of performing dot inversion with standard drivers and backplane on novel display panel layouts
US8035599B2 (en) 2003-06-06 2011-10-11 Samsung Electronics Co., Ltd. Display panel having crossover connections effecting dot inversion
US20080252581A1 (en) * 2003-06-06 2008-10-16 Samsung Electronics Co. Ltd., Liquid Crystal Display Backplane Layouts and Addressing for Non-Standard Subpixel Arrangements
US20040246404A1 (en) * 2003-06-06 2004-12-09 Elliott Candice Hellen Brown Liquid crystal display backplane layouts and addressing for non-standard subpixel arrangements
US20040246278A1 (en) * 2003-06-06 2004-12-09 Elliott Candice Hellen Brown System and method for compensating for visual effects upon panels having fixed pattern noise with reduced quantization error
US20050083277A1 (en) * 2003-06-06 2005-04-21 Credelle Thomas L. Image degradation correction in novel liquid crystal displays with split blue subpixels
US8144094B2 (en) 2003-06-06 2012-03-27 Samsung Electronics Co., Ltd. Liquid crystal display backplane layouts and addressing for non-standard subpixel arrangements
US9001167B2 (en) 2003-06-06 2015-04-07 Samsung Display Co., Ltd. Display panel having crossover connections effecting dot inversion
US8633886B2 (en) 2003-06-06 2014-01-21 Samsung Display Co., Ltd. Display panel having crossover connections effecting dot inversion
US8436799B2 (en) 2003-06-06 2013-05-07 Samsung Display Co., Ltd. Image degradation correction in novel liquid crystal displays with split blue subpixels
US20070188527A1 (en) * 2003-06-06 2007-08-16 Clairvoyante, Inc System and method for compensating for visual effects upon panels having fixed pattern noise with reduced quantization error
US20070146270A1 (en) * 2003-06-06 2007-06-28 Clairvoyante, Inc Dot Inversion on Novel Display Panel Layouts with Extra Drivers
US20050068335A1 (en) * 2003-09-26 2005-03-31 Tretter Daniel R. Generating and displaying spatially offset sub-frames
US7253811B2 (en) * 2003-09-26 2007-08-07 Hewlett-Packard Development Company, L.P. Generating and displaying spatially offset sub-frames
US20050099540A1 (en) * 2003-10-28 2005-05-12 Elliott Candice H.B. Display system having improved multiple modes for displaying image data from multiple input source formats
US7646430B2 (en) 2003-10-28 2010-01-12 Samsung Electronics Co., Ltd. Display system having improved multiple modes for displaying image data from multiple input source formats
US20060238649A1 (en) * 2003-10-28 2006-10-26 Clairvoyante, Inc Display System Having Improved Multiple Modes For Displaying Image Data From Multiple Input Source Formats
US20090102855A1 (en) * 2004-04-09 2009-04-23 Samsung Electronics Co., Ltd. Subpixel rendering filters for high brightness subpixel layouts
US7505053B2 (en) 2004-04-09 2009-03-17 Samsung Electronics Co., Ltd. Subpixel layouts and arrangements for high brightness displays
US20070257931A1 (en) * 2004-04-09 2007-11-08 Clairvoyante, Inc Subpixel rendering filters for high brightness subpixel layouts
US8390646B2 (en) 2004-04-09 2013-03-05 Samsung Display Co., Ltd. Subpixel rendering filters for high brightness subpixel layouts
US20050225574A1 (en) * 2004-04-09 2005-10-13 Clairvoyante, Inc Novel subpixel layouts and arrangements for high brightness displays
US20050225575A1 (en) * 2004-04-09 2005-10-13 Clairvoyante, Inc Novel subpixel layouts and arrangements for high brightness displays
US20050225563A1 (en) * 2004-04-09 2005-10-13 Clairvoyante, Inc Subpixel rendering filters for high brightness subpixel layouts
US7583279B2 (en) 2004-04-09 2009-09-01 Samsung Electronics Co., Ltd. Subpixel layouts and arrangements for high brightness displays
US7920154B2 (en) 2004-04-09 2011-04-05 Samsung Electronics Co., Ltd. Subpixel rendering filters for high brightness subpixel layouts
US20070070086A1 (en) * 2004-04-09 2007-03-29 Clairvoyante, Inc. Subpixel Rendering Filters for High Brightness Subpixel Layouts
US20050276502A1 (en) * 2004-06-10 2005-12-15 Clairvoyante, Inc. Increasing gamma accuracy in quantized systems
US20090080805A1 (en) * 2004-10-29 2009-03-26 Tokyo Institute Of Technology Fast Method of Super-Resolution Processing
US8009933B2 (en) * 2004-10-29 2011-08-30 Tokyo Institute Of Technology Fast method of super-resolution processing
US20060284872A1 (en) * 2005-06-15 2006-12-21 Clairvoyante, Inc Improved Bichromatic Display
US7705855B2 (en) 2005-06-15 2010-04-27 Samsung Electronics Co., Ltd. Bichromatic display
US20070045549A1 (en) * 2005-08-30 2007-03-01 Chun-Fu Wang Method for Adjusting the Visual Qualities of Images Displayed on a Monitor and Related Monitor
US7755569B2 (en) * 2005-08-30 2010-07-13 Chi Mei El Corporation Method for adjusting the visual qualities of images displayed on a monitor and related monitor
US20080049047A1 (en) * 2006-08-28 2008-02-28 Clairvoyante, Inc Subpixel layouts for high brightness displays and systems
US7876341B2 (en) 2006-08-28 2011-01-25 Samsung Electronics Co., Ltd. Subpixel layouts for high brightness displays and systems
US8018476B2 (en) 2006-08-28 2011-09-13 Samsung Electronics Co., Ltd. Subpixel layouts for high brightness displays and systems
US20080094419A1 (en) * 2006-10-24 2008-04-24 Leigh Stan E Generating and displaying spatially offset sub-frames
US8049685B2 (en) * 2006-11-09 2011-11-01 Global Oled Technology Llc Passive matrix thin-film electro-luminescent display
US20080111771A1 (en) * 2006-11-09 2008-05-15 Miller Michael E Passive matrix thin-film electro-luminescent display
US20090237530A1 (en) * 2008-03-20 2009-09-24 Ilia Ovsiannikov Methods and apparatuses for sharpening images
US20130141480A1 (en) * 2011-12-02 2013-06-06 Industrial Technology Research Institute System and method for improving visual effect of a display device
US9053557B2 (en) * 2011-12-02 2015-06-09 Industrial Technology Research Institute System and method for improving visual effect of a display device
US20170039990A1 (en) * 2015-08-05 2017-02-09 Boe Technology Group Co., Ltd. Pixel array, display device and driving method thereof, and driving device
US20170103566A1 (en) * 2015-10-12 2017-04-13 Samsung Electronics Co., Ltd. Texture processing method and unit

Also Published As

Publication number Publication date Type
KR20040096763A (en) 2004-11-17 application
JP2004334195A (en) 2004-11-25 application
JP4688432B2 (en) 2011-05-25 grant
EP1484743A2 (en) 2004-12-08 application
EP1484743A3 (en) 2006-08-09 application
KR100636658B1 (en) 2006-10-19 grant
US7110012B2 (en) 2006-09-19 grant

Similar Documents

Publication Publication Date Title
US6904169B2 (en) Method and system for improving color images
US7088392B2 (en) Digital image system and method for implementing an adaptive demosaicing method
US6970597B1 (en) Method of defining coefficients for use in interpolating pixel values
US5793885A (en) Computationally efficient low-artifact system for spatially filtering digital color images
US6262708B1 (en) Techniques for displaying complex characters
US6198467B1 (en) Method of displaying a high-resolution digital color image on a low-resolution dot-matrix display with high fidelity
EP0723364A2 (en) Real-time image enhancement techniques
US7082218B2 (en) Color correction of images
US7245326B2 (en) Method of edge based interpolation
US7362897B2 (en) Interpolation processing apparatus and recording medium having interpolation processing program recorded therein
US20090092325A1 (en) Systems and methods for selective handling of out-of-gamut color conversions
US20060038826A1 (en) Bit-depth extension of digital displays via the use of models of the impulse response of the visual system
US20030063201A1 (en) Image mosaic data reconstruction
US20090285480A1 (en) Multi-channel edge-aware chrominance noise reduction
Platt Optimal filtering for patterned displays
US20040196297A1 (en) Image data set with embedded pre-subpixel rendered image
US20020037101A1 (en) Image processing apparatus, image processing method and computer program product for correcting image obtained by shooting subject
US20100085452A1 (en) new spatio-spectral sampling paradigm for imaging and a novel color filter array design
Klompenhouwer et al. 13.4: Subpixel image scaling for color matrix displays
US20040141072A1 (en) Weighted gradient based and color corrected interpolation
US20070247532A1 (en) Image processing apparatus
US20090116750A1 (en) Color interpolation method and device
US7508448B1 (en) Method and apparatus for filtering video data using a programmable graphics processor
US20050024380A1 (en) Method for reducing random access memory of IC in display devices
US6297847B1 (en) Removal of interpolation artifacts in a non-interlaced video stream

Legal Events

Date Code Title Description
AS Assignment

Owner name: SHARP LABORATORIES OF AMERICA, INC., WASHINGTON

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:MESSING, DEAN;DALY, SCOTT J.;REEL/FRAME:014650/0095

Effective date: 20031020

AS Assignment

Owner name: SHARP KABUSHIKI KAISHA, JAPAN

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:SHARP LABORATORIES OF AMERICA, INC.;REEL/FRAME:018367/0637

Effective date: 20060929

CC Certificate of correction
CC Certificate of correction
FPAY Fee payment

Year of fee payment: 4

REMI Maintenance fee reminder mailed
FPAY Fee payment

Year of fee payment: 8

SULP Surcharge for late payment

Year of fee payment: 7

MAFP

Free format text: PAYMENT OF MAINTENANCE FEE, 12TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1553)

Year of fee payment: 12